# ======================

config_encoder = dict(
    use_radical=True,
    use_lexicon=True,
    use_synoym=False,
    multiview_feature_dim=100,
    hidden_dim=512,
    pooler_dim=100,
)
### TODO


## 这里的input_dim和hidden_dim 随着 特征的维度会变化
config_fuse = dict(
    input_dim=1368,  # [300, 768， 868, 968]
    hidden_dim=1368,  # [300, 768， 868, 968]
    num_layer=1,
)


config_classifier = dict(
    input_dim=1368,  # [300, 768, 868, 968]
    hidden_dim=512,
    pooling_type="logsumexp",  # ['sum', 'logsumexp', 'max', 'min', 'CLS']
)

config_semantic = dict(
    use_char=True,  #  CharCNN
    use_biword=True,
    char_embed_size=100,
    biword_embed_size=100,
    pooler_dim=100,
    use_bert=True,
    bert_path=r"D:\huggingface\bert-base-chinese",
    # bert_path="./hf_models/chinese-lert-base",
    # bert_path="./hf_models/chinese-macbert-large",
)

config_lexicon = dict(
    fix_embedding=False,  # 是否对于外部词典的embedding进行finetune
    use_char=True,
    use_biword=True,
    use_count=True,
    word_emb_dim=50,
    biword_emb_dim=50,
    gaz_embed_dim=50,
    pooler_dim=100,
)


config_radical = dict(
    radical_feature_dim=100,
    pooler_dim=100,
    filter_nums=[50, 30, 20],
    kernel_sozes=[5, 3, 2],
    pool_method="max",
)


# ======================

CONFIG = dict(
    config_lexicon=config_lexicon,
    config_sematic=config_semantic,
    config_radical=config_radical,
    config_encoder=config_encoder,
    config_fuse=config_fuse,
    config_classifier=config_classifier,
)
